Palaniswamy Rajan, chairman and CEO of Atlanta-based SoftWear Automation, proudly told Forbes recently. “You can have zero inventory and a batch size of 1. You can’t do that overseas. We enable seamless commerce from manufacturing to retail.” SoftWear has developed a robotic table—the sewbot—that uses machine vision to adjust to fabric stretching and distortion in the sewing process. This year, Tianyuan Garments Company—one of China’s biggest apparel makers—will open a factory in Arkansas staffed by 330 sewbots and only 400 human workers, most machine operators. The factory will produce an estimated 23 million t-shirts a year with a cost-per-shirt of 33 cents. “Around the world, even the cheapest labor market can’t compete with us,” Tang Xinhong, the chairman of Tianyuan, told China Daily about the factory.

For decades, the apparel industry has proven one of the most-resistant manufacturing sectors to automation as cheap labor, pliable materials, and complicated sewing steps fended off the robot revolution (see WILTW September 28, 2017). As of 2015, only 1,580 of the 1.63 million robots in operation worldwide were in textiles, apparel, and leather, according to the International Federation of Robotics. This has insulated the garment and textiles workforce—more than 40 million people worldwide, most low-skilled, most residing in “the Global South”—against automation. Now, we appear at a tipping point—the convergence of Digital Age consumer demand and chemical and robotics innovation.

For years, we have dissected the looming threat of widespread automation, with the disenfranchisement of low-skilled workers a preeminent concern. Some projections are near-apocalyptic—most famously, an Oxford Martin School report that estimated anywhere from 55% to 85% of jobs in the developing world are at risk of automation in the next two decades (see WILTW February 18, 2016). Yet, key questions remain up for debate: Even if automation in some industries is technologically feasible, will it be economically profitable? Can global workforces—and government policies—adapt as quickly as automation disrupts? Will robotics prove an equalizer or further empower monopolism? Over the next few years, no industry will provide more answers than apparel.

Talking to The Wall Street Journal recently, Zahid Hussain, the World Bank’s lead Bangladesh economist, encapsulated the threat of apparel-industry automation: “If you cannot absorb [young people] in productive activities, they will do something. And the something they will do may not be socially pleasant. It’s a social time bomb.”

From 2000 to 2010, Bangladeshi garment exports nearly tripled. The industry now employs roughly four million Bangladeshi workers and contributes 82% of the nation’s overall export income. Yet, according to a World Bank estimate, the nation needs two million new jobs per year to keep pace with its expanding labor force. The apparel industry already appears unlikely to meet that demand—the number of new jobs added to the garment and textile trades has fallen to 60,000 per year globally, which compares to more than 300,000 per year between 2003 and 2010.

For decades, the garment and textile industry has been a springboard for developing nations. From Taiwan, Japan, South Korea, and China after World War II to India, Mexico, Ethiopia, Indonesia, Vietnam, and Bangladesh over recent decades, the industry has played a key role in enabling the transition from agricultural to industrial economies. Automation threatens to break that springboard.

The promise of robotics to the garment and textiles industry is clear. By marginalizing labor costs, robots can enable local production in developed markets. Shipping costs are reduced. Clothing can go from development to distribution faster. Quality can be improved as human error is eliminated from the production equation. And machines can be taught to execute new fashions faster than a human labor force. As SoftWear’s Rajan summed it up to Forbes: “A nimble and local supply chain is the cure for the ills that plague the retail fashion business.”

Big, mass-market apparel brands have faced intensifying market-share threats from smaller, niche competitors, fast-fashion brands, and cheap, private-label products. Automation appears a panacea. With greater spending power, apparel giants can innovate and implement robotics faster than smaller competitors. Then, by coupling those innovations with industry-leading point-of-sale and social media data, they can more cost-effectively diagnose and meet ever-changing consumer demand.

As The Financial Times reported in a profile about Nike and its partnership with Flex, a high-tech manufacturing company developing automated knitting machines, laser-cutting, and gluing technologies for the shoe giant (see WILTW November 2, 2017):

For Nike, the shift to greater automation has two huge attractions. By driving down costs, it could lead to a dramatic improvement in profit margins. It would also allow the company to deliver new designs more quickly to fickle, fashion-conscious customers at a premium.

Furthering the automation incentive, labor costs are rising in Asia. Bangladesh, for one, raised the monthly minimum garment worker salary by 77% to $64 after the Rana Plaza garment-factory disaster, which killed more than 1,100 people when the building collapsed in 2013. As Sridhar Tayur, a professor of operations management at Carnegie Mellon’s Tepper School of Business, told the FT:

The very-low labour costs in Asia are no longer that low unless you go to Africa or somewhere else…The pressure has been mounting for a long time to either move to a super low-cost place or automate more. That has come to a point where people are more seriously looking to automation.

Yet, while the incentives are clear, many believe the threat of apparel automation is overstated. First, robots can still only handle “high-volume basics”—garments with simple, repetitive stitching and not more complicated and idiosyncratic items. Even Rajan doubts his sewbots can automate more than 20 to 25% of apparel production. Second, labor is still cheap enough in some Asian and African nations that the short-term cost of roboticizing production may outweigh the long-term benefits. This is why the world’s biggest clothing maker—China’s Crystal Group—has limited its robotics investments and is instead expanding production capacity in Bangladesh, Cambodia, Sri Lanka, and Vietnam.

Finally, there is the issue of corporate responsibility. Again, Nike is a key example. As one of the pioneers of outsourcing labor to the developing world, Nike is among the biggest multinational employers. Its factories employ 493,000 line workers in 15 countries. With contracted factories added in, that number balloons to 1.02 million workers in 42 countries.

Source: Financial Times

As Nike progressively automates production and reshores jobs to the developing world, it risks a backlash from the humans on which it will still depend in the interim: developing world employees and politicians, as well as global consumers. Again, we quote the FT:

For companies such as Nike, it opens up new political issues in the countries where it has been operating for the past two decades. The company risks being attacked for depriving jobs to its Asian workers—the same ones it was once accused of mistreating…

In these pages previously (WILTW October 13, 2016), we have quoted Our World in Data’s Max Roser regarding one of the great achievements of the modern world: “On every day in the last 25 years there could have been a newspaper headline reading, ‘The number of people in extreme poverty fell by 137,000 since yesterday.’” Widespread automation of garment and textile manufacturing could halt, if not reverse this progress, threatening destabilizing social unrest, mass migration, and more failed states.

Will the upsides of robotic production compel apparel giants, fearful of disruptive competition, to ignore the grave downsides? Or will technological feasibility and the consequences of impoverishing low-skilled labor slow the automation revolution, giving workforces and governments time to adapt? Across industry, these are questions that will define the Fourth Industrial Revolution. Apparel may be the key industry to look to for answers.